In resource management, information technology (IT) managers typically decide how much computing, storage, and network capacity will be needed to support anticipated business workloads, while being mindful of configuration costs. Capacity planning allows the IT manager to estimate these parameters. For a given configuration of computing, storage, and network infrastructure, the IT manager may manually specify anticipated workloads to decide expected utilization of a given infrastructure. However, this procedure is inefficient, time-consuming, and repetitive. Based on estimated results for each configuration, the IT manager may need to manually select and specify another configuration and estimate expected utilization again. As such, the burden is on the IT manager to manually specify a detailed hypothetical infrastructure configuration for each expected utilization. Therefore, there exists a need to improve computing infrastructure estimation techniques and reduce manually specifying hypothetical configurations.